While electric vehicles (EVs) become popular for their environmental friendliness and low fuel cost, they have not fully replaced internal combustion engine vehicles due to the risk of explosion of battery cells, the high price for the large number of battery cells required, and the limited availability of charging stations. As many researchers have pointed out, temperature is one of the most critical factors in designing and operating EVs. For example, an extremely high temperature may lead to explosion or performance degradation of battery cells. In contrast, a battery system operating at a very low temperature might be dysfunctional or have a low capacity due to low reaction rates with freezing electrolytes. In addition, the discharge rate of battery cells varies with temperature, which, in turn, varies their capacity.
To address the challenges related to temperature, most automotive manufacturers have developed their own thermal management systems for their EVs. That is, a Battery Management System (BMS) monitors the temperature of battery cells, and triggers a thermal control function when temperature deviates from a normal operational range. The thermal control includes both cooling control and heating control. Existing controls are all or nothing type controls. That is, existing controls either heat or cool all the battery cells connected in parallel regardless of each individual cell's heating and/or cooling requirement. However, such coarse-grained controls result in a large safety margin and hence inefficiency. More importantly, they do not exploit temperature for more efficient management, in that more sophisticated controls of temperature even within the normal operational range may yield better battery performance.
The goal of this disclosure is to develop thermal management for an efficient and reliable BMS. Efficiency is measured by the ratio of the useful energy delivered by a dynamic system to the energy supplied to it; this may achieve efficiency by maximizing operation-time, or the cumulative time for a BMS to provide the required power after a full battery cell charge. The BMS achieves reliability by providing a required power throughout a given battery warranty period without an explosion or malfunction, while letting its cells undergo charge-and-discharge cycles.
To improve efficiency without compromising reliability, a cyber-physical perspective of battery thermal management system that integrates and coordinates between cyber and physical battery parts is desirable. For physical parts, the battery thermal management system determines thermo-physical characteristics of battery cells and external thermal stress conditions, as they have significant impact on battery performance. By carefully accounting for these nonlinear physical properties and abstracting the characteristics in the cyber space as shown in FIG. 1a, a desirable thermal management is developed that reduces the safety margin, thereby increasing the efficiency of the entire battery system in EVs.
To achieve this goal, temperature is used as a control knob; beyond a simple temperature control only for the normal operational range, the battery thermal management system actively controls temperature for more efficient and reliable operations. This requires understanding the thermal and general issues of batteries that affect the efficiency and reliability. Therefore, issues based on a battery's thermo-physical characteristics and their impact on the electrical state of battery cells are analyzed and based on this analysis, a strategy is derived to achieving a battery thermal management system with cell-level thermal controls. The battery thermal management system boosts the performance of cells temporarily when high-power is required, while resting cells when low power is required to reduce stresses. To evaluate the proposed BMS, realistic workloads based on real driving patterns are adopted and simulated with a widely-used battery simulator. The simulation results demonstrate the effectiveness of the proposed battery thermal management, improving operation-time up to 58.4%, without sacrificing reliability, over the existing BMS.
This section provides background information related to the present disclosure which is not necessarily prior art.